Programmable Nanophotonics for Deep Learning and Neuromorphic Computing
用于深度学习和神经形态计算的可编程纳米光子学
基本信息
- 批准号:RGPIN-2018-05249
- 负责人:
- 金额:$ 2.4万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2018
- 资助国家:加拿大
- 起止时间:2018-01-01 至 2019-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
SYNOPSIS. The birth of computers shaped 20th century society and science. After decades of exponential improvement, the performance of von Neumann architectures in speed, efficiency, and generality, has begun to run into fundamental limits, as the shrinking of transistors reaches its physical limits. As a result, the gap between current computing capabilities and computing needs is widening. This insufficiency is apparent in problems involving complex systems, big data, or real-time requirements. Forays into unconventional (non-von Neumann) computing have only been partially successful due to the limitations in bandwidth and energy consumption posed by metal interconnects.******VISION & OBJECTIVES. The groundwork of the proposed program stems from my Banting Fellowship which coined the term Neuromorphic Photonics. The vision of my cross-disciplinary research is to advance the understanding of photonic physics for scalable information processing by unifying nanophotonic (i.e. optical) physics, neuromorphic (i.e. brain-inspired) architectures, and emerging technology (silicon photonics) platforms. The resulting photonic processors will have the potential to outperform state-of-the-art microelectronic processors in energy efficiency and computational speeds by seven- and four orders-of-magnitude, respectively. Scientific objectives include: 1) devices thrust—energy efficient (attoJoule/operation) photonic neurons with graphene-based electro-optic modulators; 2) architectures thrust—scalable and programmable silicon photonic neural network architectures; and 3) applications thrust—photonic processors for generalized neuromorphic computing tasks including deep learning and nonlinear optimization for model predictive control. This program focuses on these computing tasks as they are notoriously difficult to solve.******IMPACT. An experimentally-driven investigation of neuromorphic nanophotonics will serve as the first feasibility proof of using integrated photonics for scalable information processing. The proposed program has the potential to shape the emerging field of generalized compute engines beyond von-Neumann architectures and help redefine their physical limitations. The resulting technology has the potential to transform social, scientific, and technological sectors including self-navigating vehicles, bio-informatics, security, and big data. This research will contribute to the culture of innovation excellence across the scientific community and Canada. The multi-disciplinary nature of the program promises to foster collaborative ties across Canadian academic institutions and the private sector. The program's educational impact rests on uniquely positioning students for a readied workforce in academia or industry to drive tomorrow's advancements in photonics, applied physics, and engineering for 21st century challenges.
概要。计算机的诞生塑造了世纪的社会和科学。经过几十年的指数级改进,冯·诺依曼架构在速度、效率和通用性方面的性能已经开始遇到根本性的限制,因为晶体管的缩小达到了其物理极限。因此,当前计算能力与计算需求之间的差距正在扩大。这种不足在涉及复杂系统、大数据或实时要求的问题中很明显。由于金属互连带来的带宽和能耗限制,对非常规(非冯·诺依曼)计算的尝试只取得了部分成功。愿景与愿景。这个计划的基础来自我的班廷奖学金,它创造了神经形态光子学这个术语。我的跨学科研究的愿景是通过统一纳米光子(即光学)物理学,神经形态(即大脑启发)架构和新兴技术(硅光子学)平台来推进对光子物理学的理解,以实现可扩展的信息处理。由此产生的光子处理器将有可能在能源效率和计算速度方面分别超过最先进的微电子处理器七个和四个数量级。科学目标包括:1)具有基于石墨烯的电光调制器的推进能量有效(阿托焦耳/操作)光子神经元的设备; 2)推进可扩展和可编程硅光子神经网络架构的架构;以及3)用于广义神经形态计算任务的推进光子处理器的应用,包括深度学习和模型预测控制的非线性优化。这个程序专注于这些计算任务,因为它们是出了名的难以解决。冲击神经形态纳米光子学的实验驱动的调查将作为使用集成光子学进行可扩展信息处理的第一个可行性证明。拟议的计划有可能塑造冯-诺伊曼架构之外的通用计算引擎新兴领域,并帮助重新定义其物理限制。由此产生的技术有可能改变社会,科学和技术领域,包括自导航车辆,生物信息学,安全和大数据。这项研究将有助于整个科学界和加拿大的创新卓越文化。该计划的多学科性质有望促进加拿大学术机构和私营部门的合作关系。该计划的教育影响取决于独特的定位学生在学术界或工业界的准备劳动力,以推动未来的光子学,应用物理学和工程的进步,为21世纪的挑战。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Shastri, Bhavin其他文献
Advances in photonic neuromorphic computing (Conference Presentation)
光子神经形态计算的进展(会议演讲)
- DOI:
10.1117/12.2509838 - 发表时间:
2019 - 期刊:
- 影响因子:0
- 作者:
Sorger, Volker J.;George, Jonathan K.;Mehrabian, Armin;Shastri, Bhavin;El-Ghazawi, Tarek;Prucnal, Paul R.;Lee, El-Hang;He, Sailing - 通讯作者:
He, Sailing
Shastri, Bhavin的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Shastri, Bhavin', 18)}}的其他基金
Programmable Nanophotonics for Deep Learning and Neuromorphic Computing
用于深度学习和神经形态计算的可编程纳米光子学
- 批准号:
RGPIN-2018-05249 - 财政年份:2022
- 资助金额:
$ 2.4万 - 项目类别:
Discovery Grants Program - Individual
Cryogenic system for the exploration of low-temperature neuromorphic photonic systems
用于探索低温神经形态光子系统的低温系统
- 批准号:
RTI-2022-00457 - 财政年份:2021
- 资助金额:
$ 2.4万 - 项目类别:
Research Tools and Instruments
Programmable Nanophotonics for Deep Learning and Neuromorphic Computing
用于深度学习和神经形态计算的可编程纳米光子学
- 批准号:
RGPIN-2018-05249 - 财政年份:2021
- 资助金额:
$ 2.4万 - 项目类别:
Discovery Grants Program - Individual
Programmable Nanophotonics for Deep Learning and Neuromorphic Computing
用于深度学习和神经形态计算的可编程纳米光子学
- 批准号:
RGPIN-2018-05249 - 财政年份:2020
- 资助金额:
$ 2.4万 - 项目类别:
Discovery Grants Program - Individual
Excitable logic for photonic information processing
光子信息处理的可兴奋逻辑
- 批准号:
543613-2019 - 财政年份:2019
- 资助金额:
$ 2.4万 - 项目类别:
Engage Grants Program
Neurophotonic-electronic brain-machine interface system
神经光子电子脑机接口系统
- 批准号:
RTI-2020-00407 - 财政年份:2019
- 资助金额:
$ 2.4万 - 项目类别:
Research Tools and Instruments
Programmable Nanophotonics for Deep Learning and Neuromorphic Computing
用于深度学习和神经形态计算的可编程纳米光子学
- 批准号:
RGPIN-2018-05249 - 财政年份:2019
- 资助金额:
$ 2.4万 - 项目类别:
Discovery Grants Program - Individual
Programmable Nanophotonics for Deep Learning and Neuromorphic Computing
用于深度学习和神经形态计算的可编程纳米光子学
- 批准号:
DGECR-2018-00208 - 财政年份:2018
- 资助金额:
$ 2.4万 - 项目类别:
Discovery Launch Supplement
Photonic cortical processor using graphene and silicon nanophotonics for complex systems analysis
使用石墨烯和硅纳米光子学进行复杂系统分析的光子皮质处理器
- 批准号:
469008-2014 - 财政年份:2015
- 资助金额:
$ 2.4万 - 项目类别:
Banting Postdoctoral Fellowships Tri-council
Photonic cortical processor using graphene and silicon nanophotonics for complex systems analysis
使用石墨烯和硅纳米光子学进行复杂系统分析的光子皮质处理器
- 批准号:
469008-2014 - 财政年份:2014
- 资助金额:
$ 2.4万 - 项目类别:
Banting Postdoctoral Fellowships Tri-council
相似海外基金
Quantum Nanophotonics with Atomically Thin Materials
原子薄材料的量子纳米光子学
- 批准号:
FT220100053 - 财政年份:2023
- 资助金额:
$ 2.4万 - 项目类别:
ARC Future Fellowships
Equipment: MRI: Track #1 Acquisition of Photonic Wirebonding Tool for Quantum and Nanophotonics
设备: MRI:轨道
- 批准号:
2320265 - 财政年份:2023
- 资助金额:
$ 2.4万 - 项目类别:
Standard Grant
REU Site: Nanophotonics, Quantum Photonics, and Vision/Biomedical Optics at the University of Rochester.
REU 站点:罗切斯特大学的纳米光子学、量子光子学和视觉/生物医学光学。
- 批准号:
2244031 - 财政年份:2023
- 资助金额:
$ 2.4万 - 项目类别:
Standard Grant
ExpandQISE: Track 1: Development of Er-doped Semiconductor Nanophotonics to realize Optoelectronic Capabilities for Quantum Information Applications at Telecom Wavelengths
ExpandQISE:轨道 1:开发掺铒半导体纳米光子学以实现电信波长量子信息应用的光电功能
- 批准号:
2328540 - 财政年份:2023
- 资助金额:
$ 2.4万 - 项目类别:
Standard Grant
Nonlinear topological nanophotonics based on semiconductor photonic crystals
基于半导体光子晶体的非线性拓扑纳米光子学
- 批准号:
22H00298 - 财政年份:2022
- 资助金额:
$ 2.4万 - 项目类别:
Grant-in-Aid for Scientific Research (A)
Nanophotonics for telecom quantum networks based on neutral silicon vacancy centers in diamond
基于金刚石中性硅空位中心的电信量子网络纳米光子学
- 批准号:
545932-2020 - 财政年份:2022
- 资助金额:
$ 2.4万 - 项目类别:
Postgraduate Scholarships - Doctoral
Dissipative mode theories and reservoir engineering in quantum nanophotonics
量子纳米光子学中的耗散模式理论和储层工程
- 批准号:
RGPIN-2020-04069 - 财政年份:2022
- 资助金额:
$ 2.4万 - 项目类别:
Discovery Grants Program - Individual
Exploring concepts in nanophotonics and metamaterials to create a 'super-scintillator' for time-of-flight positron emission tomography
探索纳米光子学和超材料概念,创建用于飞行时间正电子发射断层扫描的“超级闪烁体”
- 批准号:
10509318 - 财政年份:2022
- 资助金额:
$ 2.4万 - 项目类别:
CAREER: Scalable Integrated Nanophotonics with Subwavelength Gratings
职业:具有亚波长光栅的可扩展集成纳米光子学
- 批准号:
2144568 - 财政年份:2022
- 资助金额:
$ 2.4万 - 项目类别:
Continuing Grant